code: def _get_initial_decoder_states(self, gnn_output: GnnOutput):
      return self.__node_to_graph_representation(
          ElementsToSummaryRepresentationInput(
              element_embeddings=torch.cat(
                  (
                      gnn_output.input_node_representations,
                      gnn_output.output_node_representations,
                  ),
                  dim=-1,
              ),
              element_to_sample_map=gnn_output.node_to_graph_idx,
              num_samples=gnn_output.num_graphs,
          )
      )
  
imports: from typing_extensions import Final, TypedDict
  import torch
  from typing import Any, Dict, List, NamedTuple, Optional, Tuple, Union
  from ptgnn.baseneuralmodel import AbstractNeuralModel, ModuleWithMetrics
  from ptgnn.baseneuralmodel.utils.data import enforce_not_None
  from ptgnn.neuralmodels.gnn.graphneuralnetwork import GraphNeuralNetwork, GraphNeuralNetworkModel
  from ptgnn.neuralmodels.gnn.structs import GnnOutput, GraphData, TensorizedGraphData
  from ptgnn.neuralmodels.reduceops import AbstractVarSizedElementReduce, ElementsToSummaryRepresentationInput, MultiheadSelfAttentionVarSizedElementReduce, SimpleVarSizedElementReduce
  from ptgnn.neuralmodels.sequence.grucopydecoder import DecoderData, GruCopyingDecoder, GruCopyingDecoderModel, TokenizedOutput
label_desc: Use image node_id 4 for calling the Graph2SeqModule obj's underlying member method code with example usage: obj._get_initial_decoder_states(gnn_output) and returns: self